Urgent position of ETL Tester with AI Experience (Only Local)

Hi,
Urgent position of ETL Tester with AI Experience (Only Local)
Chicago, IL (Hybrid – 3 days’ Work from Office)
Looking for a Senior QA professional skilled in ETL, SQL, Azure Databricks, Agentic AI evaluation, web testing, and test automation tools, driving data integrity, compliance, and scalable validation strategies to join our team in Chicago, IL
Roles and Responsibilities: –
· We are building AI agents that generate the extraction queries and transformation logic instead plus the Workbench through which humans review and approve everything they produce.
· The agents emit metadata; the client’s existing data platform executes it. What you’ll do Own test strategy and reconciliation methodology Define the equivalence standard: what must match exactly, what may vary within tolerance, and at which layer each applies Design source-to-target validation across the redesigned path — raw ingestion, consolidated transformation, domain refined
· Establish risk-based prioritisation; the schedule does not permit exhaustive coverage of hundreds of tables Author the Test Strategy and Test Plan for review with the client in Phase 2 Own agent evaluation Build and maintain a golden reference set from existing production extracts, validated with the Epic SME, with strict separation between evaluation data and anything used to develop or tune the agents Stand up the evaluation harness in MLflow — scoring runs, versioning, candidate comparison
· Define and report the measures that matter mapping precision and recall, override rate, confidence calibration, run-to-run consistency, escalation correctness and cost per case Operate the regression gate — no prompt, skill or model change is promoted without passing evaluation.
· A prompt change can silently degrade quality with no data-level symptom Characterise how agents fail, not just how often: hallucinated tables, plausible-but-wrong column
· Confirm optimised queries touch fewer source tables than baseline and that facility consolidation genuinely works Lead and report Direct two QA engineers; set standards, review coverage, own the defect taxonomy
· Confirm downstream compatibility across Databricks, SQL Server and Vertica Produce evidence packs suitable for client executive review, and defend methodology, sample sizes and statistical claims under scrutiny.
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